scholarly journals Unmanned Aerial Patrol Technology Based on Tracking Algorithm of Target Tracking

2018 ◽  
Vol 14 (11) ◽  
pp. 160
Author(s):  
Yao Yao ◽  
Qing-le Quan ◽  
Hong-hui Zhang ◽  
Qiong Li
Keyword(s):  
Kalman Filter ◽  
Machine Vision ◽  
Target Tracking ◽  
Unmanned Aerial Vehicle ◽  
Transmission Lines ◽  
Region Of Interest ◽  
Power Line ◽  
Tracking Algorithm ◽  
Inspection Method ◽  
Aerial Vehicle

<p class="0abstract"><span lang="EN-US">In order to study the power patrol technology of unmanned aerial vehicle, the tracking algorithm was applied. The automatic patrolling of power lines was discussed in terms of algorithms. An unmanned aerial vehicle transmission line inspection method based on machine vision was proposed. The image and video of the unmanned aerial vehicle inspection of the power line had a complex background. By Wiener filtering de-noising and probability density functions, the image clarity was improved. According to the existing tracking techniques and algorithms, a Camshaft target tracking algorithm based on lossless Kalman filter was proposed. The method of non-destructive Kalman filter was adopted to predict the region of interest of power line identification. Using the Camshaft algorithm, the prediction of the window was searched and the size of the window was adjusted. Transmission lines were tracked in real time. The results showed that the restoration effect of the algorithm was obvious. The clarity of the image was improved. It prepared for the extraction and tracking of the future transmission lines. Therefore, the proposed method provides a feasible way for the UAV power line inspection technology based on machine vision.</span></p>

scholarly journals Unmanned Aerial Vehicle Video-Based Target Tracking Algorithm Using Sparse Representation

2019 ◽  
Vol 6 (6) ◽  
pp. 9689-9706 ◽  
Author(s):  
Minjie Wan ◽  
Guohua Gu ◽  
Weixian Qian ◽  
Kan Ren ◽  
Xavier Maldague ◽  
...  
Keyword(s):  
Sparse Representation ◽  
Target Tracking ◽  
Unmanned Aerial Vehicle ◽  
Tracking Algorithm ◽  
Aerial Vehicle

Development of Wire Suspended Robot System (ARANEUS 2.0) for Bridge Inspection

10.29007/zw9k ◽  
2020 ◽  
Author(s):  
Kazuhide Nakata ◽  
Kazuki Umemoto ◽  
Kenji Kaneko ◽  
Ryusuke Fujisawa
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Concrete Surface ◽  
Wire Length ◽  
High Definition ◽  
Bridge Inspection ◽  
Robot System ◽  
Inspection Method ◽  
Aerial Vehicle ◽  
The Wire

This study addresses the development of a robot for inspection of old bridges. By suspending the robot with a wire and controlling the wire length, the movement of the robot is realized. The robot mounts a high-definition camera and aims to detect cracks on the concrete surface of the bridge using this camera. An inspection method using an unmanned aerial vehicle (UAV) has been proposed. Compared to the method using an unmanned aerial vehicle, the wire suspended robot system has the advantage of insensitivity to wind and ability to carry heavy equipments, this makes it possible to install a high-definition camera and a cleaning function to find cracks that are difficult to detect due to dirt.

Power Transmission Lines Inspection using Properly Equipped Unmanned Aerial Vehicle (UAV)

2018 ◽  
Author(s):  
Alexandros Zormpas ◽  
Konstantia Moirogiorgou ◽  
Kostas Kalaitzakis ◽  
George A. Plokamakis ◽  
Panayotis Partsinevelos ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Transmission Lines ◽  
Power Transmission ◽  
Power Transmission Lines ◽  
Aerial Vehicle

Dynamic gyroscope sensors fusion and calibration using Kalman filter

2018 ◽  
Vol 7 (2.3) ◽  
pp. 18
Author(s):  
Mishell D. Lawas ◽  
Sherwin A. Guirnaldo
Keyword(s):  
Kalman Filter ◽  
Unmanned Aerial Vehicle ◽  
Systems Design ◽  
Mean Square ◽  
Fusion Technique ◽  
System Experiment ◽  
Aerial Vehicle ◽  
Sensors Fusion ◽  
The Stability ◽  
Actual Test

The stability of an Unmanned Aerial Vehicle (UAV) during actual flight conditions is one parameter that is very important in systems design in Avionics. In this research, two sensors, the autopilot microcontroller and the smartphone gyroscope sensing mechanism, are fused together and calibrated to monitor the flying behavior of the UAV prior to actual test flights. The two fused sensors and installed inside the UAV for relatively increased sensing accuracy and best flight monitoring capabilities. A Kalman filter is used as fusion technique and a Stewart Motion tracker is also used to test the ruggedness and accuracy of the fused sensor system. Experiment results show that fused system can give an overall mean square error or 1.9729.

scholarly journals Aplikasi Machine Vision pada Hexacopter untuk Deteksi Survival Kits di Bidang Mitigasi Bencana

2020 ◽  
Vol 12 (2) ◽  
pp. 72-79
Author(s):  
Ismawan Noor Ikhsan ◽  
Son Ali Akbar
Keyword(s):  
Machine Vision ◽  
Color Space ◽  
Region Of Interest ◽  
Contour Detection ◽  
Segmentation Method ◽  
Smart System ◽  
Hsv Color Space ◽  
Aerial Vehicle ◽  
Detection Evaluation ◽  
Flying Robots

Hexacopter belongs to one of flying robots that is used to carry out a special mission such as retrieving and delivering survival kits object. Thus, it should be built by smart system to determine the object accurately. However, there was an interference from other object that made it difficult to recognize the survival kits object. Therefore, the development of machine vision with the integration of the hexacopter control system is expected to improve the object recognition process. This study intends to develop a survival kit detection using the image processing method, which involved 1) segmentation on the Hue, Saturation, Value (HSV) color space, 2) contour detection, and 3) Region of Interest (ROI) selected detection. The evaluation of the segmentation method performances was done through the three-part experiments (i.e., the similar shape, variety of a color object, and an object shape). The result of survival kits object detection evaluation obtained an accuracy of 90.33%, precision of 99.63%, and recall of 91.24%. According to the performances obtained in this study, the development of machine vision systems on Unmanned Aerial Vehicle (UAV) has a high accuracy for the object survival kits detection even with another object interference.

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